300 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "Simons Foundation" Postdoctoral positions in United Kingdom
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machine learning methods to model changes in the brain over the lifespan, including brain structure and function, and how those changes relate to environment and genomics. About the Role The post is funded
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Interviews are expected to take place on 29 April 2026 RCA Benefits available here: https://www.rca.ac.uk/more/work-at-the-rca/staff-benefits/ The Royal College of Art (RCA) aims to foster an inclusive
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electrophysiology data obtained through collaborations and perform cross-species comparisons. We use machine learning techniques for neural data analysis and computational modelling with a special interest in
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dissemination of results through publications and presentations. Find out more about the O’Hare research and group at: https://ohare.chem.ox.ac.uk About you Applicants must hold a PhD in Chemistry or a relevant
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their surfaces. Machine learning methods are used to close the complexity gap. Currently, the group consists of three full professors, one associate professor, 6 postdocs and about 15 PhD and 7 master
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, including exoplanet studies, machine learning, cutting-edge radio instrumentation and digital signal processing, citizen science, sky surveys, and studies of transient and variable objects. Listen is deeply
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The opportunity The University of Liverpool is a key partner in a £14 million initiative ( https://tinyurl.com/yc5z768m ) to develop a sustainable, next-generation manufacturing facility, using
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the sequence of the human genome and the development of common diseases. You will work on a collaborative project that aims to develop Machine Learning and laboratory-based approaches, for decoding how the human
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, machine learning, or data analytics. As a proficient programmer (ideally Python), you will be curiosity-led, with exceptional communication skills, and thrive in a highly interdisciplinary environment. You
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connectivity and network neuroscience measures? Can machine learning models trained on high-quality clinical data be adapted to work effectively with lower-quality data from community settings? For more